// 用户实体类
@Entity
public class User {@Id @GeneratedValueprivate Long id;private String username;private String password; // 存储BCrypt加密后的密码private String phone;private String openid; // 微信openidprivate String avatar;private Date createTime;// getters/setters省略
}// 注册接口
@PostMapping("/register")
public ResponseEntity<?> register(@RequestBody RegisterDTO dto) {if (userRepository.existsByUsername(dto.getUsername())) {return ResponseEntity.badRequest().body("用户名已存在");}User user = new User();user.setUsername(dto.getUsername());user.setPassword(passwordEncoder.encode(dto.getPassword()));user.setCreateTime(new Date());userRepository.save(user);return ResponseEntity.ok("注册成功");
}// JWT登录过滤器（微信/手机号登录共用）
public class JwtAuthenticationFilter extends OncePerRequestFilter {@Overrideprotected void doFilterInternal(HttpServletRequest req, HttpServletResponse res, FilterChain chain) throws ServletException, IOException {try {String token = getTokenFromRequest(req);if (token != null && validateToken(token)) {String username = getUsernameFromToken(token);UsernamePasswordAuthenticationToken auth = new UsernamePasswordAuthenticationToken(username, null, authorities);SecurityContextHolder.getContext().setAuthentication(auth);}} catch (Exception e) {logger.error("认证失败", e);}chain.doFilter(req, res);}
}

// 前端（uni-app）
async handlePhoneLogin() {const { code } = await uni.login();const { encryptedData, iv } = await uni.getPhoneNumber({success: res => res});const { data } = await http.post('/api/auth/phone', { code, encryptedData, iv });uni.setStorageSync('token', data.token);
}// 后端（Spring Boot）
@PostMapping("/phone")
public ResponseEntity<?> phoneLogin(@RequestBody PhoneLoginDTO dto) {// 1. 通过code获取微信session_keyWxSession session = wxService.getSessionInfo(dto.getCode());// 2. 解密手机号String phone = AesUtil.decrypt(dto.getEncryptedData(), session.getSessionKey(), dto.getIv());// 3. 查找或创建用户User user = userRepository.findByPhone(phone).orElseGet(() -> createUserFromPhone(phone));// 4. 生成JWTString token = jwtUtil.generateToken(user);return ResponseEntity.ok(new LoginResponse(token, user));
}

CREATE TABLE category (id BIGINT PRIMARY KEY AUTO_INCREMENT,name VARCHAR(50) NOT NULL COMMENT '分类名称',sort INT DEFAULT 0 COMMENT '排序字段'
);CREATE TABLE tag (id BIGINT PRIMARY KEY AUTO_INCREMENT,name VARCHAR(20) NOT NULL COMMENT '标签名称',type TINYINT COMMENT '1:题材 2:风格 3:情感'
);CREATE TABLE drama_tag (drama_id BIGINT NOT NULL,tag_id BIGINT NOT NULL,PRIMARY KEY (drama_id, tag_id)
);

// 视频处理服务
@Service
public class VideoProcessingService {@Value("${ffmpeg.path}")private String ffmpegPath;public void transcodeVideo(MultipartFile source, String outputPath) throws IOException {String tempPath = "/tmp/" + UUID.randomUUID() + ".mp4";source.transferTo(new File(tempPath));// 生成多码率视频String cmd = String.format("%s -i %s -c:v libx264 -crf 23 -preset fast " +"-profile:v baseline -level 3.0 -s 640x360 -b:v 500k -maxrate 500k -bufsize 1000k " +"-c:a aac -b:a 128k -ar 44100 -f mp4 %s",ffmpegPath, tempPath, outputPath);Process process = Runtime.getRuntime().exec(cmd);process.waitFor();// 生成封面图String thumbCmd = String.format("%s -i %s -ss 00:00:01 -vframes 1 -q:v 2 %s",ffmpegPath, tempPath, outputPath.replace(".mp4", ".jpg"));Runtime.getRuntime().exec(thumbCmd).waitFor();new File(tempPath).delete();}
}

# 基于用户的协同过滤推荐
import numpy as np
from sklearn.metrics.pairwise import cosine_similarityclass Recommender:def __init__(self):self.user_item_matrix = Noneself.user_sim = Nonedef fit(self, ratings):# ratings: DataFrame(userId, dramaId, rating)self.user_item_matrix = ratings.pivot_table(index='userId', columns='dramaId', values='rating').fillna(0)# 计算用户相似度self.user_sim = pd.DataFrame(cosine_similarity(self.user_item_matrix),index=self.user_item_matrix.index,columns=self.user_item_matrix.index)def recommend(self, user_id, n=5):if user_id not in self.user_sim.index:return []# 获取相似用户sim_users = self.user_sim[user_id].sort_values(ascending=False)[1:11]# 计算加权评分weighted_scores = []for other_user, sim in sim_users.items():other_ratings = self.user_item_matrix.loc[other_user]weighted_scores.append(other_ratings * sim)# 合并结果并排除已观看agg_scores = pd.concat(weighted_scores).groupby(level=1).sum()watched = set(self.user_item_matrix.loc[user_id][self.user_item_matrix.loc[user_id] > 0].index)recommendations = agg_scores[~agg_scores.index.isin(watched)]return recommendations.sort_values(ascending=False).head(n).index.tolist()

// 前端（Vue3 + Socket.IO）
const socket = io('https://yourdomain.com/danmu');
socket.on('connect', () => {console.log('弹幕服务已连接');
});function sendDanmu() {socket.emit('send', {dramaId: currentDrama.id,content: inputValue.value,color: color.value,time: player.currentTime});inputValue.value = '';
}// 后端（Node.js）
const io = require('socket.io')(server, {cors: { origin: "*" }
});io.of('/danmu').on('connection', (socket) => {console.log('用户连接:', socket.id);socket.on('send', (data) => {// 验证用户权限if (!validateUser(socket.handshake.auth.token)) {return socket.disconnect(true);}// 存储弹幕到Redisredis.zadd(`danmu:${data.dramaId}`, data.time, JSON.stringify({id: uuidv4(),content: data.content,color: data.color,userId: socket.handshake.auth.userId,createTime: Date.now()}));// 广播给同剧集用户socket.to(`drama:${data.dramaId}`).emit('receive', data);});socket.on('join', (dramaId) => {socket.join(`drama:${dramaId}`);// 发送历史弹幕（最近5分钟）const now = Date.now();redis.zrangebyscore(`danmu:${dramaId}`, now - 300000, now, (err, replies) => {if (!err) replies.forEach(msg => socket.emit('receive', JSON.parse(msg)));});});
});